20 citations · 37 across the 10 of their papers we have counts for
12 papers
Learning Task and Motion Plans from Real Demonstrations with Hybrid Flow Matching
Zuleika Redondo Garcia, Andreu Matoses Gimenez, Javier Alonso-Mora
Long-horizon mobile manipulation requires a task plan and the motion that executes it. Generative planners trained on demonstration produce both in one pass, requiring neither a sy…
Flow Policies as Actions of Skill-Level World Models: Learned and Symbolic Abstractions for Long-Horizon Planning
Andreu Matoses Gimenez, Andrei-Carlo Papuc, Chris Pek +1
Latent world models enable robots to plan by predicting the consequences of actions. Planning long tasks with control-rate actions requires many prediction steps, which enlarges th…
Curve-Induced Dynamical Systems on Riemannian Manifolds and Lie Groups
Saray Bakker, Martin Schonger, Tobias Löw +2
Deploying robots in household environments requires safe, adaptable, and interpretable behaviors that respect the geometric structure of tasks. Often represented on Lie groups and…
Impact-Robust Posture Optimization for Aerial Manipulation
Amr Afifi, Ahmad Gazar, Javier Alonso-Mora +2
We present a novel method for optimizing the posture of kinematically redundant torque-controlled robots to improve robustness during impacts. A rigid impact model is used as the b…
Global End-Effector Pose Control of an Underactuated Aerial Manipulator via Reinforcement Learning
Shlok Deshmukh, Javier Alonso-Mora, Sihao Sun
Aerial manipulators, which combine robotic arms with multi-rotor drones, face strict constraints on arm weight and mechanical complexity. In this work, we study a lightweight 2-deg…
Cross-Entropy Optimization of Physically Grounded Task and Motion Plans
Andreu Matoses Gimenez, Nils Wilde, Chris Pek +1
Autonomously performing tasks often requires robots to plan high-level discrete actions and continuous low-level motions to realize them. Previous TAMP algorithms have focused main…
Decentralized Real-Time Planning for Multi-UAV Cooperative Manipulation via Imitation Learning
Shantnav Agarwal, Javier Alonso-Mora, Sihao Sun
Existing approaches for transporting and manipulating cable-suspended loads using multiple UAVs along reference trajectories typically rely on either centralized control architectu…
SADCHER: Scheduling using Attention-based Dynamic Coalitions of Heterogeneous Robots in Real-Time
Jakob Bichler, Andreu Matoses Gimenez, Javier Alonso-Mora
We present Sadcher, a real-time task assignment framework for heterogeneous multi-robot teams that incorporates dynamic coalition formation and task precedence constraints. Sadcher…
Decentralized Aerial Manipulation of a Cable-Suspended Load using Multi-Agent Reinforcement Learning
Jack Zeng, Andreu Matoses Gimenez, Eugene Vinitsky +2
This paper presents the first decentralized method to enable real-world 6-DoF manipulation of a cable-suspended load using a team of Micro-Aerial Vehicles (MAVs). Our method levera…
Agile and Cooperative Aerial Manipulation of a Cable-Suspended Load
Sihao Sun, Xuerui Wang, Dario Sanalitro +3
Quadrotors can carry slung loads to hard-to-reach locations at high speed. Since a single quadrotor has limited payload capacities, using a team of quadrotors to collaboratively ma…
Reinforcement Learning from Simulation to Real World Autonomous Driving using Digital Twin
Kevin Voogd, Jean Pierre Allamaa, Javier Alonso-Mora +1
Reinforcement learning (RL) is a promising solution for autonomous vehicles to deal with complex and uncertain traffic environments. The RL training process is however expensive, u…
A message-passing algorithm for multi-agent trajectory planning
Jose Bento, Nate Derbinsky, Javier Alonso-Mora +1
We describe a novel approach for computing collision-free \emph{global} trajectories for agents with specified initial and final configurations, based on an improved version of…